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  • Open Access

    ARTICLE

    Design of 400 V-10 kV Multi-Voltage Grades of Dual Winding Induction Generator for Grid Maintenance Vehicle

    Tiankui Sun*, Shuyi Zhuang, Yongling Lu, Wenqiang Xie, Ning Guo, Sudi Xu

    Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070213 - 27 December 2025

    Abstract To ensure an uninterrupted power supply, mobile power sources (MPS) are widely deployed in power grids during emergencies. Comprising mobile emergency generators (MEGs) and mobile energy storage systems (MESS), MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies, offering advantages such as flexibility and high resilience through electricity delivery via transportation networks. This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator (DWIG) intended for MEG applications, employing an improved particle swarm optimization (PSO) algorithm based on a back-propagation neural network (BPNN). A… More >

  • Open Access

    REVIEW

    Human Behaviour Classification in Emergency Situations Using Machine Learning with Multimodal Data: A Systematic Review (2020–2025)

    Mirza Murad Baig1, Muhammad Rehan Faheem2,*, Lal Khan3,*, Hannan Adeel2, Syed Asim Ali Shah4

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 2895-2935, 2025, DOI:10.32604/cmes.2025.073172 - 23 December 2025

    Abstract With growing urban areas, the climate continues to change as a result of growing populations, and hence, the demand for better emergency response systems has become more important than ever. Human Behaviour Classification (HBC) systems have started to play a vital role by analysing data from different sources to detect signs of emergencies. These systems are being used in many critical areas like healthcare, public safety, and disaster management to improve response time and to prepare ahead of time. But detecting human behaviour in such stressful conditions is not simple; it often comes with noisy… More > Graphic Abstract

    Human Behaviour Classification in Emergency Situations Using Machine Learning with Multimodal Data: A Systematic Review (2020–2025)

  • Open Access

    ARTICLE

    Sustainable Emergency Rescue Products: Design and Monitoring Techniques for Preventing and Mitigating Construction Failures in Unforeseen Circumstances

    Xiaobo Jiang, Hongchao Zheng*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1695-1716, 2025, DOI:10.32604/sdhm.2025.063890 - 17 November 2025

    Abstract Construction failures caused by unforeseen circumstances, such as natural disasters, environmental degradation, and structural weaknesses, present significant challenges in achieving durability, safety, and sustainability. This research addresses these challenges through the development of advanced emergency rescue systems incorporating wood-derived nanomaterials and IoT-enabled Structural Health Monitoring (SHM) technologies. The use of nanocellulose which demonstrates outstanding mechanical capabilities and biodegradability alongside high resilience allowed developers to design modular rescue systems that function effectively even under challenging conditions while providing real-time failure protection. Experimental data from testing showed that the replacement system strengthened load-bearing limits by 20% while… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Detection of DDoS Attacks in VANETs for Emergency Vehicle Communication

    Bappa Muktar*, Vincent Fono, Adama Nouboukpo

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4705-4727, 2025, DOI:10.32604/cmc.2025.067733 - 23 October 2025

    Abstract Vehicular Ad Hoc Networks (VANETs) are central to Intelligent Transportation Systems (ITS), especially for real-time communication involving emergency vehicles. Yet, Distributed Denial of Service (DDoS) attacks can disrupt safety-critical channels and undermine reliability. This paper presents a robust, scalable framework for detecting DDoS attacks in highway VANETs. We construct a new dataset with Network Simulator 3 (NS-3) and Simulation of Urban Mobility (SUMO), enriched with real mobility traces from Germany’s A81 highway (OpenStreetMap). Three traffic classes are modeled: DDoS, Voice over IP (VoIP), and Transmission Control Protocol Based (TCP-based) video streaming (VideoTCP). The pipeline includes normalization,… More >

  • Open Access

    ARTICLE

    Barriers and Facilitators to Implementation of Mindfulness in Motion for Firefighters and Emergency Medical Service Providers

    Beth Steinberg1,*, Yulia Mulugeta1, Catherine Quatman-Yates2, Maeghan Williams2, Anvitha Gogineni1, Maryanna Klatt1

    International Journal of Mental Health Promotion, Vol.27, No.9, pp. 1237-1264, 2025, DOI:10.32604/ijmhp.2025.067232 - 30 September 2025

    Abstract Background: Community-based first responders face high levels of workplace stressors that can profoundly impact their physical and mental health. Mindfulness-based interventions have shown promise in decreasing stress and increasing psychological resilience; however, implementation is difficult due to unpredictability of the job, department culture, and generational preferences. The objective of this qualitative study was to identify and enhance understanding of the specific needs and potential barriers and facilitators for the implementation of mindfulness-based programming for community-based first responders. Methods: A phenomenological qualitative study design was used to gain insights into the lived experiences of first responders… More >

  • Open Access

    ARTICLE

    Coordinated Charging Scheduling Strategy for Electric Vehicles Considering Vehicle Urgency

    Zhenhao Wang1, Hongwei Li1,*, Dan Pang2, Jinming Ge1

    Energy Engineering, Vol.122, No.8, pp. 3223-3242, 2025, DOI:10.32604/ee.2025.063615 - 24 July 2025

    Abstract Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles, this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use. First, considering the range loss characteristics, dynamic time-sharing tariff mechanism, and user incentive policy in the low-temperature environment of northern winter, a differentiated charging model is constructed for four types of vehicles: family cars, official cars, buses, and cabs. Then, we innovatively introduce the… More >

  • Open Access

    ARTICLE

    The Emergency Control Method for Multi-Scenario Sub-Synchronous Oscillation in Wind Power Grid Integration Systems Based on Transfer Learning

    Qing Zhu1, Denghui Guo1, Rui Ruan1, Zhidong Chai1, Chaoqun Wang2, Zhiwen Guan2,*

    Energy Engineering, Vol.122, No.8, pp. 3133-3154, 2025, DOI:10.32604/ee.2025.063165 - 24 July 2025

    Abstract This study presents an emergency control method for sub-synchronous oscillations in wind power grid-connected systems based on transfer learning, addressing the issue of insufficient generalization ability of traditional methods in complex real-world scenarios. By combining deep reinforcement learning with a transfer learning framework, cross-scenario knowledge transfer is achieved, significantly enhancing the adaptability of the control strategy. First, a sub-synchronous oscillation emergency control model for the wind power grid integration system is constructed under fixed scenarios based on deep reinforcement learning. A reward evaluation system based on the active power oscillation pattern of the system is… More >

  • Open Access

    ARTICLE

    An Integrated Perception Model for Predicting and Analyzing Urban Rail Transit Emergencies Based on Unstructured Data

    Liang Mu1, Yurui Kang1, Zixu Yan1, Guangyu Zhu2,*

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2495-2512, 2025, DOI:10.32604/cmc.2025.063208 - 03 July 2025

    Abstract The accurate prediction and analysis of emergencies in Urban Rail Transit Systems (URTS) are essential for the development of effective early warning and prevention mechanisms. This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data. To address issues related to data structuredness and missing values, we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network (ER-GAIN) for data structuring and imputation. Additionally, to mitigate the impact of imbalanced data on the predictive performance of emergencies, we introduced an Adaptive Boosting Ensemble… More >

  • Open Access

    ARTICLE

    A Data-Enhanced Deep Learning Approach for Emergency Domain Question Intention Recognition in Urban Rail Transit

    Yinuo Chen1, Xu Wu1, Jiaxin Fan1, Guangyu Zhu2,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1597-1613, 2025, DOI:10.32604/cmc.2025.062779 - 09 June 2025

    Abstract The consultation intention of emergency decision-makers in urban rail transit (URT) is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services. This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions. However, the current structured degree of the URT emergency knowledge base remains low, and the domain questions lack labeled datasets, resulting in a large deviation between the consultation outcomes and the intended objectives. To address this issue, this paper proposes a question intention recognition model for the URT emergency domain,… More >

  • Open Access

    ARTICLE

    Emergency room management of urolithiasis: a sex-based comparison

    Mark Shilling1, Lauren S. Faber2, Hoi Doan2, Merry Peckham2, Timothy R. Petersen1,3, Reza Ehsanian1, Frances Alba2,*

    Canadian Journal of Urology, Vol.32, No.2, pp. 81-88, 2025, DOI:10.32604/cju.2025.063415 - 30 April 2025

    Abstract Introduction: Existing literature has highlighted disparities in acute pain management across racial and sex groups in both emergency department and pre-hospital settings. This study aimed to evaluate prescribing patterns among physicians and advanced practice providers for patients with upper tract urolithiasis in an academic emergency department. Materials and Methods: Retrospective chart review of patients diagnosed with upper tract urolithiasis was performed to evaluate age, sex, race, ethnicity, stone size and location, presence of hydronephrosis, admission status, history of prior nephrolithiasis, medications administered in the emergency department (ED), requests for urology consult or referral, and discharge medications. More >

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